二、VOC可视化数据集
1、作用
在做目标检测时,首先要检查标注数据。一方面是要了解标注的情况,另一方面是检查数据集的标注和格式是否正确,只有正确的情况下才能进行下一步的训练。
2、代码实现
import os # import sys import cv2 import random from tqdm import tqdm # import numpy as np import argparse import xml.etree.ElementTree as ET def xml_reader(filename): """ Parse a PASCAL VOC xml file """ tree = ET.parse(filename) objects = [] for obj in tree.findall('object'): obj_struct = {} obj_struct['name'] = obj.find('name').text bbox = obj.find('bndbox') obj_struct['bbox'] = [int(bbox.find('xmin').text), int(bbox.find('ymin').text), int(bbox.find('xmax').text), int(bbox.find('ymax').text)] objects.append(obj_struct) return objects def get_image_list(image_dir, suffix=['jpg', 'png']): '''get all image path ends with suffix''' if not os.path.exists(image_dir): print("PATH:%s not exists" % image_dir) return [] imglist = [] for root, sdirs, files in os.walk(image_dir): if not files: continue for filename in files: filepath = os.path.join(root, filename) if filename.split('.')[-1] in suffix: imglist.append(filepath) return imglist if __name__ == "__main__": parser = argparse.ArgumentParser(description='check data') parser.add_argument('--input', dest='input', help='The input dir of images', type=str) parser.add_argument('--output', dest='output', default='temp', help='The output dir of images', type=str) parser.add_argument('--num', dest='num', default=50, help='The number of images you want to check', type=int) args = parser.parse_args() if not os.path.exists(args.output): os.makedirs(args.output) img_list = get_image_list(args.input) img_list = random.sample(img_list, args.num) for img_path in tqdm(img_list): img = cv2.imread(img_path) if img is None or not img.any(): continue xml_path = img_path.replace("JPEGImages", "Annotations").replace(".jpg", ".xml").replace(".png", ".xml") objects = xml_reader(xml_path) if len(objects) == 0: continue # draw box and name for obj in objects: name = obj['name'] box = obj['bbox'] p1 = (box[0], box[1]) p2 = (box[2], box[3]) p3 = (max(box[0], 15), max(box[1], 15)) cv2.rectangle(img, p1, p2, (0, 0, 255), 2) cv2.putText(img, name, p3, cv2.FONT_ITALIC, 1, (0, 255, 0), 2) img_name = os.path.basename(img_path) cv2.imwrite(os.path.join(args.output, img_name), img)
3、使用方法
python Visual_dataset.py --input VOCdevkit/JPEGImages --output ./Result_imgs --num 3408 python 上述代码的文件名称 --input 图片地址 --output 输出文件夹地址 --num 图片数量
4、常见报错
(python38) D:\pythontorch\VOC>python Visual_dataset.py --input VOCdevkit/ImageSets --output Result_imgs --num 3408
Traceback (most recent call last):
File "Visual_dataset.py", line 55, in <module>
img_list = random.sample(img_list, args.num)
File "C:\ProgramData\Anaconda3\envs\python38\lib\random.py", line 363, in sample
raise ValueError("Sample larger than population or is negative")
ValueError: Sample larger than population or is negative
原因 你的路径写错了